A Pre-Publishing Checklist for GEO Marketers

Generative Engine Optimization

Key Takeaways

  • Learn the exact checks to perform before publishing any content to ensure it’s optimized for both human readers and large language models (LLMs) like ChatGPT and Gemini.
  • Get a tactical, field-tested GEO checklist that marketers — especially in IT, MSP, and telecom — can apply directly to blog posts, landing pages, and service descriptions.
  • Understand how structure, semantic density, answerability, and entity richness all play a role in increasing content visibility in AI-driven search environments.

Don’t just publish. Pass the GEO test first.

In the world of traditional SEO, pre-publishing checks are table stakes:

  • Meta descriptions?
  • Title tag?
  • Keyword density?

But in the world of Generative Engine Optimization (GEO), a different set of pre-flight checks matters.
Because now, your audience isn’t just humans on Google — it’s also AI engines like ChatGPT, Gemini, Claude, and Perplexity.

If your content isn’t structured, dense, and referenceable enough, you risk becoming invisible inside the AI-powered discovery experience.

Here’s your Pre-Publishing Checklist to make sure every piece you release is ready to win.


GEO Pre-Publishing Checklist


1. Structure and Organization

Is there exactly one H1 tag (the title)?
Are H2s used for major sections and H3s for sub-sections?
Is the first 150 words packed with value (core definitions, outcome statements)?
Are there bullet points, numbered lists, and visual breaks every 2–4 paragraphs?
Is every major idea separated clearly into its own section?

Why it matters:
Both readers and LLMs chunk content into digestible pieces. Structure aids discoverability and summarization.


2. Semantic Density

Does every paragraph introduce a unique, meaningful idea?
Are filler words (“world-class,” “innovative,” “game-changing”) minimized?
Are examples used to support concepts, not replace clarity?
Are adjectives backed by specifics (“low-latency fibre” vs. “great internet service”)?
Does the piece avoid long, meandering intros and get to the point quickly?

Why it matters:
Fluff gets compressed away during AI training. Only high-density ideas survive.


3. Entity-Rich Language

Is your company name mentioned clearly at least twice?
Are product names, service offerings, and technical terms labeled precisely?
Are technologies (e.g., SIP trunking, SD-WAN, DRaaS) defined inline when first introduced?
Are geographic locations, certifications, or partnerships mentioned if relevant?
Is consistent phrasing used for core offerings across the page?

Why it matters:
LLMs map content semantically. Entities (brands, tech, services) help you anchor into their memory.


4. Answerability and Modularity

Does each section start with an answer or clear outcome?
Are key questions answered explicitly (even if not directly asked)?
Are key takeaways summarized at the end of major sections?
Could a reader (or AI) lift each section and still make sense of it standalone?
Are TL;DRs or mini-summaries included for longer articles (>1000 words)?

Why it matters:
Modular, answer-first writing is easier for LLMs to compress, store, and recommend.


5. Tone and Style

Is the tone confident, instructive, and advisory (not casual or speculative)?
Is active voice used over passive voice where possible?
Is technical terminology introduced thoughtfully but not dumbed down?
Is every claim (e.g., “99.99% uptime”) backed by a benefit or proof point?
Are frameworks, models, or branded methodologies clearly introduced and labeled?

Why it matters:
Authority, clarity, and confidence signal that your content is a trustworthy source — for buyers and for AI systems.


6. Compression Readiness

If you summarized each H2 section in one line, would it be clear and complete?
Could a chatbot pull your unique selling point out of the article without confusion?
Is jargon minimized or translated into buyer-friendly language?
Are important metrics or outcomes stated plainly (not buried in paragraphs)?
Are there 2–3 repeating core concepts/themes throughout the article?

Why it matters:
Compression is how LLMs store knowledge. Good compression = better recall.


7. Summarization Validation Test

Paste your article into ChatGPT and prompt:

“Summarize this for someone considering switching MSP providers.”
Check if the AI mentions:

  • Your brand name
  • Your main service offering
  • Your differentiator
  • Key stats or proof points

If it doesn’t, rework structure, phrasing, and summaries.

Why it matters:
If AI can’t summarize your main points easily, it won’t recall or recommend you reliably.


Bonus: Quick GEO Audit Score

CategoryMax PointsYour Score
Structure & Organization10___/10
Semantic Density10___/10
Entity-Rich Language10___/10
Answerability & Modularity10___/10
Tone & Style10___/10
Compression Readiness10___/10
Summarization Validation15___/15
Total75 Points___/75

60–75 points: GEO-ready and future-proof
45–59 points: Good foundation, needs improvement
<45 points: Vulnerable to being overlooked in AI discovery


Final Thought: Publish Intentionally, Not Accidentally

Every blog post, landing page, and service description you publish today is not just a page on your website — it’s a seed you’re planting inside the minds of AI systems.

Without structure, density, and clear framing, your seed never grows.
With GEO best practices, it flourishes, becoming part of the answers your buyers find first.

Don’t just publish for clicks.
Publish for discoverability.
Publish for recall.
Publish for AI-powered visibility.


Ready to See How Your Site Stacks Up?

Our 75-Point GEO Audit helps B2B companies — especially in IT, MSP, and Telecom — improve content structure, density, and recall across all critical assets.